The present application relates to improved methods and systems for calibrating image rendering systems that deliver digital images on multiple media. It finds particular application in conjunction with document processing and image processing systems, and it will be described with particular reference thereto. However, it is to be appreciated that, some embodiments are amenable to other applications.
By way of background, it is known that media properties can affect the color response of a printer because of toner, surface and optical characteristics. One of the reasons different substrates can have different responses to the marking process is that they can have different spectral characteristics. Spectral characteristics are the way things respond to light. In the case of a printable substrate, it is how the substrate reflects, absorbs, and scatters light. Color reproduced in a glossy white substrate and a dark textured substrate is quite different.
To obtain consistent print quality across multiple media, different media specific color correction look up tables (LUTs) may be supported. Generally, these LUTs are constructed a priori using spectrophotometer measurements for known media. They are stored in the digital front end controller for use while RIPping the document. Full re-characterization on each media generally gives the best quality. However, when a printer is supported with a large media set (e.g., greater than 400 media), re-characterization on each media is very time consuming. Also, a typical user may print on 5 to 20 media in 1 day. Gray balance calibration is performed on a single media (e.g., DCG) in present systems such as iGen systems manufactured by Xerox Corporation. Although gray balance calibration on each media can further improve color quality (mostly along neutral), re-characterization is preferred since with re-characterization all the print engine colors can be improved. Even after using inline sensors, re-characterization on each media becomes time-consuming particularly for color-critical and time-critical customers. Within the print jobs, a reduced media set and color is preferred for re-characterization or gray balance calibration. An improved method of automatic optimal or near optimal (sub-optimal) media selection for use by the operator or the machine prior to printing multiple media job is considered very valuable.
Typically, the user must recreate and change the color management LUTs and/or marking process parameters whenever media substrates change. It takes considerable experience to properly fine tune the LUTs or change marking parameters to obtain optimal performance. The required level of expertise is high and can lead to high cost to print shop vendors.
In U.S. application Ser. No. 11/125,897, filed May 9, 2005, entitled “METHOD TO AUTOMATICALLY IDENTIFY AND COMPENSATE FOR SUBSTRATE DIFFERENCES USING A SENSOR,” by Lalit K. Mestha, et al., a method of calculating the degree of similarity between the test media substrate and all the pre-characterized substrates stored in the broad media database by using from the sensor measurements some measured media attributes (e.g., spectral reflectance of the substrate, special characteristics such as media fluorescence, other non-color-related attributes such as surface roughness, weight, thickness, gloss, etc.) was disclosed. A substrate from the database is chosen that is most similar to the test substrate along the chosen attribute. The test substrate then inherits the pre-built color correction LUTs that are associated with the chosen database substrate, which may then be used for managing color of the given job just before printing. This feature would be useful for many production printers to find the right media type so that jobs can be automatically re-routed on correct media.
However, there is a need for identifying the best media out of the set being considered so that re-characterization or re-calibration can be performed on minimal number of media set to obtain/reconstruct the most up-to-date color management LUT from those already available in the database. The approach described below can further improve the color quality on the media since at the time the customer wishes to print the printer state is measured and image colors are adjusted automatically for reproducing the best color when compared to using the old color management LUT that was created in the factory.